Bachelor
2024/2025
Introduction into Python
Type:
Elective course (Foreign Languages and Intercultural Communication)
Area of studies:
Linguistics
Delivered by:
School of Foreign Languages
Where:
School of Foreign Languages
When:
2 year, 2, 3 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Maksim Karpov
Language:
English
ECTS credits:
3
Course Syllabus
Abstract
Python is one of the most popular and easy to learn programming languages. This language is a powerful data analysis tool, which may increase efficiency of almost any activity in science or industry. Python may help automise routine operations and process data in the amount, which is by several orders higher than the amount achievable manually or with the use of the electronic spreadsheets. This module is aimed at developing skills in the area of understanding the code and writing own programs. It will cover the topics essential for the study of the basic types of data and syntactic constructions of Python, as well as for the preparation to an independent programming test of the entry and basic level. This module is taught on the basis of the course “Python as a foreign language” (in Russian: «Python как иностранный») https://edu.hse.ru/course/view.php?id=133389
Learning Objectives
- Learning by the students of the basics of the Python programming language, which are sufficient to understand somebody else’s code and to write own simple programs.
Expected Learning Outcomes
- Create variables, turn data into variables, address variables
- Define types of data of Python correctly and convert them, if necessary
- Work with the lines, use indexing and formatting of the lines.
- Understand the errors displayed by the software and fix them.
- Identify mistakes in other people’s code and fix them.
- Use logical data type, comparison operators, logical operators.
- Write own conditional constructs.
- Use loops to process repeating actions, terminate loop upon condition.
- Use loops to iterate sequences.
- Understand the logic behind the functioning of a loop.
- Distinguish between mutable and immutable types of data; understand, which methods may be applied to them.
- Conduct operations with the sets, interpret the results in a meaningful way.
- Create a dictionary and add data into it; conduct search in a dictionary.
- Store and address data within the nested structures.
- Sort sequences, sort dictionaries by the keys and values.
- Import ready functions and use them.
- Write own functions and use them.
- Find mistakes in other people’s functions and fix them.
- Open and create text files.
- Calculate, process and analyse data from the files.
- Perform suggested algorithm of problem solving.
- Develop own algorithm of problem solving and perform it.
Course Contents
- Introduction to programming. Key data types. Creation of variables. Most common mistakes.
- Logical data type. Conditional constructs.
- While loop. Operators break and continue. Use of else in the loop.
- For loop. Lists and tuples. Map()function.
- Method of lines and lists.
- Sets. Operations with sets. Set methods.
- Dictionaries. Dictionary methods. Nested structures.
- Sorting, .sorted() function.
- Work with the functions.
- Work with the text and spreadsheet files.
Assessment Elements
- Control WorkThe tasks are writing code. The student's assignment is checked against open and hidden data. The examples of tasks are similar to the examples of independent work. The demo version of the test is publicly available no later than seven days before the activity.
- ExamThe exam is conducted remotely online with proctoring using two cameras (one from a computer, the other from a smartphone).
- Project and project defenceIt is performed in groups of 3 people. A group of 1-2 people can be organized, but only in exceptional cases, in consultation with the teacher. The project is the writing of a well-functioning application program followed by mandatory oral defense.
- Mini-tests
- Individual Works
Interim Assessment
- 2024/2025 3rd module0.2 * Control Work + 0.2 * Exam + 0.2 * Individual Works + 0.1 * Mini-tests + 0.3 * Project and project defence
Bibliography
Recommended Core Bibliography
- Learning Python : [covers Python 2.5], Lutz, M., 2008
Recommended Additional Bibliography
- 9781491912140 - Vanderplas, Jacob T. - Python Data Science Handbook : Essential Tools for Working with Data - 2016 - O'Reilly Media - https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1425081 - nlebk - 1425081